Cleaning an Orders Dataset with PySpark

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Updated 07/2024

Step into a data engineer's shoes and master data cleaning with PySpark on an e-commerce orders dataset!

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Project Description

Data cleaning is an essential skill for any data professional.

In this project, you will step into a role of a data engineer at an e-commerce company and use PySpark, a powerful tool for data processing, to clean an orders dataset.

This hands-on experience will sharpen your ability to format, extract and amend data for further analysis.

Project Tasks

1
Task 1

Technologies

Spark

Topics

Data Engineering Data Preparation

Prerequisites

Cleaning Data with PySpark

Rufat Mustafaev

Data Scientist, Booking.com

Rufat is a data scientist at the global travel-tech leader. He has a background in Economics and has applied data science to solve complex problems in various industries including management consulting, credit risk, fintech and foodtech.

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